Karan Sharma

This paper proposes that knowledge based systems must be designed as
complex adaptive systems and any other approach is not fundamental, even
if it sometimes yields good results. Complex systems are
characterized
as having global behavior not always explainable from local behavior.
Here we propose that the way we perceive knowledge in AI needs to change
to Complex Adaptive, hence the need for a paradigm shift is stressed.

Almost all historical KBS were not complex systems in an authentic
sense. But it is not a good idea to criticize them because with
available resources and theories, they did their best. Sooner or later,
we will have to design our KBS as complex adaptive systems, so why not
sooner. There are three mechanisms that must be part of any knowledge
based system, viz., Interdependency and fluidity, mechanisms for
attribution of emergent properties, and self-organization.

Karan Sharma was the author of this paper which will be
presented
at
The First Conference on Artificial General Intelligence
and
is pursuing his M.S. in Artificial Intelligence at the University of
Georgia. Currently, he is working on theoretical foundations
of Fluid Reasoning and Representations that will aid in the creation of
Artificial General Intelligence. He strongly believes that the time has
come to renounce traditional cul-de-sac rigid AI in favor of more fluid
and plastic approaches.